Speaker change detection device and speaker change detection method

A speaker change detection method comprising:

• extracting, by a processor, features representing features of human voice in each frame having a predetermined time length from a voice signal including a conversation between a plurality of speakers;
• setting, by the processor, for each of a plurality of different time points in the voice signal, a first analysis period before the time point and a second analysis period after the time point;
• generating, by the processor, for each of the plurality of time points, a first speaker model representing features of voices of a group of at least two speakers speaking in the first analysis period on the basis of a distribution of the features of a plurality of frames included in the first analysis period and a second speaker model representing features of voices of a group of at least two speakers speaking in the second analysis period on the basis of a distribution of the features in a plurality of frames included in the second analysis period;
• calculating, by the processor, for each of the plurality of time points, a matching score representing the likelihood of similarity of features between the group of speakers in the first analysis period and the group of speakers in the second analysis period by applying the features in a plurality of frames included in the second analysis period to the first speaker model and applying the features of a plurality of frames included in the first analysis period to the second speaker model;
• and
• detecting, by the processor, a speaker change point at which a change from a group of speakers speaking before the speaker change point to another group of speakers speaking after the speaker change point occurs in the voice signal on the basis of the matching score for each of the plurality of time points.

A non-transitory computer-readable recording medium having recorded thereon a speaker change detection computer program that causes a computer to execute a process comprising:

• extracting features representing features of human voice in each frame having a predetermined time length from a voice signal including a conversation between a plurality of speakers;
• setting, for each of a plurality of different time points in the voice signal, a first analysis period before the time point and a second analysis period after the time point;
• generating, for each of the plurality of time points, a first speaker model representing features of voices of a group of at least two speakers speaking in the first analysis period on the basis of a distribution of the features of a plurality of frames included in the first analysis period and a second speaker model representing features of voices of a group of at least two speakers speaking in the second analysis period on the basis of a distribution of the features in a plurality of frames included in the second analysis period;
• calculating, for each of the plurality of time points, a matching score representing the likelihood of similarity of features between the group of speakers in the first analysis period and the group of speakers in the second analysis period by applying the features in a plurality of frames included in the second analysis period to the first speaker model and applying the features of a plurality of frames included in the first analysis period to the second speaker model;
• and
• detecting a speaker change point at which a change from a group of speakers speaking before the speaker change point to another group of speakers speaking after the speaker change point occurs in the voice signal on the basis of the matching score for each of the plurality of time points.